1. School of Information Engineering, Shandong University,Weihai 264209, China; 2. Bio-Computing Research Center, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055, China; 3. Key Laboratory of Network Oriented Intelligent Computation, Shenzhen 518055, China
Blind source extraction (BSE) is particularly attractive to solve blind signal mixture problems where only a few source signals are desired. Many existing BSE methods do not take into account the existence of noise and can only work well in noise-free environments. In practice, the desired signal is often contaminated by additional noise. Therefore, we try to tackle the problem of noisy component extraction. The reference signal carries enough prior information to distinguish the desired signal from signal mixtures. According to the useful properties of Gaussian moments, we incorporate the reference signal into a negentropy objective function so as to guide the extraction process and develop an improved BSE method. Extensive computer simulations demonstrate its validity in the process of revealing the underlying desired signal.
. Noisy component extraction with reference[J]. Frontiers of Computer Science, 2013, 7(1): 135-144.
Yongjian ZHAO, Hong HE, Jianxun Mi. Noisy component extraction with reference. Front Comput Sci, 2013, 7(1): 135-144.
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